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Prediction of photovoltaic energy production using machine learning methods in the RapidMiner application
Title Prediction of photovoltaic energy production using machine learning methods in the RapidMiner application Author Hassankhani Dolatabadi Sepideh SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Co-authors Budinská Ivana 1964- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Balogh Zoltán 1976- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Mojžiš Ján 1985- SAVINFO - Ústav informatiky SAV SCOPUS RID ORCID Hassankhani Dolatabadi Saeid Source document INES 2022 : 26th IEEE international conference on intelligent engineering systems 2022 : Proceedings. P. 21-26. - Danvers, US : IEEE, 2022 / Szakál Anikó Language eng - English Country US - United States of America Document kind rozpis článkov z periodík (rzb) Citations GONG, L. - HUANG, F. - ZHANG, W. - LI, Y.M. - LIU, C.L. Precise Short-Term Small-Area Sunshine Forecasting for Optimal Seedbed Scheduling in Plant Factories. In AGRICULTURE-BASEL. SEP 2023, vol. 13, no. 9. Dostupné na: https://doi.org/10.3390/agriculture13091790. DOLATABADI, Saeid Hassankhani - OLCER, Aykut I. - VAKILI, Seyedvahid. The Application of Hybrid Energy system (Hydrogen Fuel cell, wind, and solar) in shipping. In RENEWABLE ENERGY FOCUS, 2023, vol. 46, no., pp. 197-206. ISSN 1755-0084. Dostupné na: https://doi.org/10.1016/j.ref.2023.05.008. Category ADMB - Scientific papers in foreign non-impacted journals registered in Web of Sciences or Scopus Category of document (from 2022) V2 - Vedecký výstup publikačnej činnosti ako časť editovanej knihy alebo zborníka Type of document príspevok z podujatia Year 2022 Registered in SCOPUS DOI 10.1109/INES56734.2022.9922608 
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